Provided is an image processing system capable of estimating a three-dimensional shape of a semiconductor pattern or a particle by solving problems of measurement reduction in a height direction and taking an enormous amount of time at a time of acquiring learning data. The image processing system according to the disclosure stores a detectable range of a detector provided in a charged particle beam device in a storage device in advance, generates a simulated image of a three-dimensional shape pattern using the detectable range, and learns a relationship between the simulated image and the three-dimensional shape pattern in advance.

Methods include holding a sample with a movement stage configured to rotate the sample about a rotation axis, directing an imaging beam to a first sample location with the sample at a first rotational position about the rotation axis and detecting a first transmitted imaging beam image, rotating the sample using the movement stage about the rotation axis to a second rotational position, and directing the imaging beam to a second sample location by deflecting the imaging beam in relation to an optical axis of the imaging beam and detecting a second transmitted imaging beam image, wherein the second sample location is spaced apart from the first sample location at least at least in relation to the optical axis. Related systems and apparatus are also disclosed.

The disclosure relates to a method of imaging a specimen using a transmission charged particle microscope, said method comprising providing a specimen, and providing a charged particle beam and directing said charged particle beam onto said specimen for generating a flux of charged particles transmitted through the specimen. The method comprises the step of generating and recording a first energy filtered flux of charged particles transmitted through the specimen, wherein said first energy filtered flux of charged particles substantially consists of non-scattered and elastically scattered charged particles. The method as disclosed herein comprises the further step of generating and recording a second energy filtered flux of charged particles transmitted through the specimen, wherein said second energy filtered flux of charged particles substantially consists of inelastically scattered charged particles. Said first and second recorded energy filtered flux are then used for imaging said specimen with increased contrast.

A method and system for processing a diffraction pattern image obtained in an electron microscope are disclosed. The method comprises, according to a first set of microscope conditions, causing an electron beam to impinge upon a calibration specimen so as to cause resulting electrons to be emitted therefrom and monitoring the resulting electrons using a detector device so as to obtain a calibration image comprising a plurality of pixels having values, the first set of microscope conditions being configured such that the calibration image includes substantially no electron diffraction pattern; obtaining, from the calibration image, a gain variation image comprising a plurality of pixels, each having a value representing relative detector device gain for a corresponding pixel of the calibration image; according to a second set of microscope conditions, causing an electron beam to impinge upon a target specimen so as to cause resulting electrons to be emitted therefrom and monitoring the resulting electrons using the detector device so as to obtain a target image comprising a plurality of pixels having values, the second set of microscope conditions being configured such that the target image includes an electron diffraction pattern; and for each pixel of the target image, removing from the pixel value, in accordance with the value of the corresponding pixel of the gain variation image, the contribution to the pixel value of the relative detector device gain, so as to obtain a gain variation-corrected image.

Methods and systems for creating TEM lamella using image restoration algorithms for low keV FIB images are disclosed. An example method includes irradiating a sample with an ion beam at low keV settings, generating a low keV ion beam image of the sample based on emissions resultant from irradiation by the ion beam, and then applying an image restoration model to the low keV ion beam image of the sample to generate a restored image. The sample is then localized within the restored image, and a low keV milling of the sample is performed with the ion beam based on the localized sample within the restored image.

Disclosed herein are CPM support systems, as well as related apparatuses, methods, computing devices, and computer-readable media. For example, in some embodiments, a charged particle microscope computational support apparatus may include: first logic to, for each angle of a plurality of angles, receive an associated image of a specimen at the angle, and generate an associated scan mask based on one or more regions-of-interest in the associated image; second logic to, for each angle of the plurality of angles, generate an associated data set of the specimen by processing data from a scan, in accordance with the associated scan mask, by a charged particle microscope of the specimen at the angle; and third logic to provide, for each angle of the plurality of angles, the associated data set of the specimen to reconstruction logic to generate a three-dimensional reconstruction of the specimen.

Disclosed herein are methods, apparatuses, systems, and computer-readable media related to defective pixel management in charged particle microscopy. For example, in some embodiments, a charged particle microscope support apparatus may include: first logic to identify a defective pixel region of a charged particle camera, wherein the charged particle camera cannot detect charged particle events in the defective pixel region; second logic to generate a first charged particle event indicator that identifies a first time and a first location of a first charged particle event outside the defective pixel region, wherein the first charged particle event is detected by the charged particle camera; third logic to generate a second charged particle event indicator that identifies a second time and a second location in the defective pixel region; and fourth logic to output data representative of the charged particle event indicators.

A sample holder retains a sample and can continuously rotate the sample in a single direction while the sample is exposed to a charged particle beam (CPB) or other radiation source. Typically, the CPB is strobed to produce a series of CPB images at random or arbitrary angles of rotation. The sample holder can rotate more than one complete revolution of the sample. The CPB images are used in tomographic reconstruction, and in some cases, relative rotation angles are used in the reconstruction, without input of an absolute rotation angle.

The present disclosure provides a method of transferring alignment information from a first set of images to a second set of images, a respective computer program product and a respective inspection device. A first set of cross-section images in a first imaging mode is obtained, the first cross-section images being taken at times Tai. A second set of cross-section images in a second imaging mode is obtained, the second cross-section images being taken at times Tbj, the times Tbj differing from the times Tai. Obtaining the first and second sets of cross-section images comprises subsequently removing a cross-section surface layer of a sample to make a new cross-section accessible for imaging, and imaging the new cross-section of the sample in the first imaging mode or in the second imaging mode. Switching is performed between the first and second imaging modes while obtaining the first and second sets of cross-section images.

The present invention discloses an imaging method and an apparatus for direct electron detection cameras and a computer device, and relates to the technical field of electron microscope cameras. The present invention is mainly capable of improving the signal-to-noise ratio (SNR) of an image so as to improve the detective quantum efficiency of electron. The method includes the steps of classifying clusters in an original image to obtain low SNR clusters and high SNR clusters; performing three-dimensional reconstruction by using the images corresponding to the low SNR clusters and the high SNR clusters, respectively, to obtain three-dimensional models corresponding to the low SNR clusters and the high SNR clusters, respectively; performing filtering on the image corresponding to the low SNR clusters by using the filtering function, and superimposing the image to obtain m output image corresponding to the vitrified sample.